Kailin Tan

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kailin Tan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Alex Krizhevsky
  2. Gisle Bjøntegaard
  3. E. Arıkan
  4. David Burth Kurka

Papers from Kailin Tan's perspective

Ordered by how strongly the researchers Kailin Tan trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Learning Multiple Layers of Features from Tiny Images
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Layer Normalization
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Going deeper with convolutions
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers